BackgroundThe COVID-19 pandemic has disrupted delivery of immunisation services globally. Many countries have postponed vaccination campaigns out of concern about infection risks to staff delivering vaccination, the children being vaccinated and their families. The World Health Organization recommends considering both the benefit of preventive campaigns and the risk of SARS-CoV-2 transmission when making decisions about campaigns during COVID-19 outbreaks, but there has been little quantification of the risks. MethodsWe modelled excess SARS-CoV-2 infection risk to vaccinators, vaccinees and their caregivers resulting from vaccination campaigns delivered during a COVID-19 epidemic. Our model used population age-structure and contact patterns from three exemplar countries (Burkina Faso, Ethiopia, and Brazil). It combined an existing compartmental transmission model of an underlying COVID-19 epidemic with a Reed-Frost model of SARS-CoV-2 infection risk to vaccinators and vaccinees. We explored how excess risk depends on key parameters governing SARS-CoV-2 transmissibility, and aspects of campaign delivery such as campaign duration, number of vaccinations, and effectiveness of personal protective equipment (PPE) and symptomatic screening. ResultsInfection risks differ considerably depending on the circumstances in which vaccination campaigns are conducted. A campaign conducted at the peak of a SARS-CoV-2 epidemic with high prevalence and without special infection mitigation measures could increase absolute infection risk by 32% to 45% for vaccinators, and 0.3% to 0.5% for vaccinees and caregivers. However, these risks could be reduced to 3.6% to 5.3% and 0.1% to 0.2% respectively by use of PPE that reduces transmission by 90% (as might be achieved with N95 respirators or high-quality surgical masks) and symptomatic screening. ConclusionsSARS-CoV-2 infection risks to vaccinators, vaccinees and caregivers during vaccination campaigns can be greatly reduced by adequate PPE, symptomatic screening, and appropriate campaign timing. Our results support the use of adequate risk mitigation measures for vaccination campaigns held during SARS-CoV-2 epidemics, rather than cancelling them entirely.
Initial COVID-19 containment in the United States focused on limiting mobility, including school and workplace closures. However, these interventions have had enormous societal and economic costs. Here we demonstrate the feasibility of an alternative control strategy, test-trace-quarantine: routine testing of primarily symptomatic individuals, tracing and testing their known contacts, and placing their contacts in quarantine. We performed this analysis using Covasim, an open-source agent-based model, which was calibrated to detailed demographic, mobility, and epidemiological data for the Seattle region from January through June 2020. With current levels of mask use and schools remaining closed, we found that high but achievable levels of testing and tracing are sufficient to maintain epidemic control even under a return to full workplace and community mobility and with low vaccine coverage. The easing of mobility restrictions in June 2020 and subsequent scale-up of testing and tracing programs through September provided real-world validation of our predictions. Although we show that test-trace-quarantine can control the epidemic in both theory and practice, its success is contingent on high testing and tracing rates, high quarantine compliance, relatively short testing and tracing delays, and moderate to high mask use. Thus, in order for test-trace-quarantine to control transmission with a return to high mobility, strong performance in all aspects of the program is required.
BackgroundAbsolute numbers of COVID-19 cases and deaths reported to date in the sub-Saharan Africa (SSA) region have been significantly lower than those across the Americas, Asia, and Europe. As a result, there has been limited information about the demographic and clinical characteristics of deceased cases in the region, as well as the impacts of different case management strategies. MethodsData from deceased cases reported across SSA through May 10, 2020 and from hospitalized cases in Burkina Faso through April 15, 2020 were analyzed. Demographic, epidemiological, and clinical information on deceased cases in SSA was derived through a line-list of publicly available information and, for cases in Burkina Faso, from aggregate records at the Center Hospitalier Universitaire de Tengandogo in Ouagadougou. A synthetic case population was derived probabilistically using distributions of age, sex, and underlying conditions from populations of West African countries to assess individual risk factors and treatment effect sizes. Logistic regression analysis was conducted to evaluate the adjusted odds of survival for patients receiving oxygen therapy or convalescent plasma, based on therapeutic effectiveness observed for other respiratory illnesses. ResultsAcross SSA, deceased cases for which demographic data are available have been predominantly male (63/103, 61.2%) and over 50 years of age (59/75, 78.7%). In Burkina Faso, specifically, the majority of deceased cases either did not seek care at all or were hospitalized for a single day (59.4%, 19/32); hypertension and diabetes were often reported as underlying conditions. After adjustment for sex, age, and underlying conditions in the synthetic case population, the odds of mortality for cases not receiving oxygen therapy was significantly higher than those receiving oxygen, such as due to disruptions to standard care (OR: 2.07; 95% CI: 1.56 - 2.75). Cases receiving convalescent plasma had 50% reduced odds of mortality than those who did not (95% CI: 0.24 - 0.93). ConclusionInvestment in sustainable production and maintenance of supplies for oxygen therapy, along with messaging around early and appropriate use for healthcare providers, caregivers, and patients could reduce COVID-19 deaths in SSA. Further investigation into convalescent plasma is warranted, as data on its effectiveness specifically in treating COVID-19 becomes available. The success of supportive or curative clinical interventions will depend on earlier treatment seeking, such that community engagement and risk communication will be critical components of the response.
The COVID-19 pandemic has created an urgent need for models that can project epidemic trends, explore intervention scenarios, and estimate resource needs. Here we describe the methodology of Covasim (COVID-19 Agent-based Simulator), an open-source model developed to help address these questions. Covasim includes country-specific demographic information on age structure and population size; realistic transmission networks in different social layers, including households, schools, workplaces, long-term care facilities, and communities; age-specific disease outcomes; and intrahost viral dynamics, including viral-load-based transmissibility. Covasim also supports an extensive set of interventions, including non-pharmaceutical interventions, such as physical distancing and protective equipment; pharmaceutical interventions, including vaccination; and testing interventions, such as symptomatic and asymptomatic testing, isolation, contact tracing, and quarantine. These interventions can incorporate the effects of delays, loss-to-follow-up, micro-targeting, and other factors. Implemented in pure Python, Covasim has been designed with equal emphasis on performance, ease of use, and flexibility: realistic and highly customized scenarios can be run on a standard laptop in under a minute. In collaboration with local health agencies and policymakers, Covasim has already been applied to examine epidemic dynamics and inform policy decisions in more than a dozen countries in Africa, Asia-Pacific, Europe, and North America.
BackgroundThe first case of COVID-19 in sub-Saharan Africa (SSA) was reported by Nigeria on February 27, 2020. While case counts in the entire region remain considerably less than those being reported by individual countries in Europe, Asia, and the Americas, SSA countries remain vulnerable to COVID morbidity and mortality due to systemic healthcare weaknesses, less financial resources and infrastructure to address the new crisis, and untreated comorbidities. Variation in preparedness and response capacity as well as in data availability has raised concerns about undetected transmission events. MethodsConfirmed cases reported by SSA countries were line-listed to capture epidemiological details related to early transmission events into and within countries. Data were retrieved from publicly available sources, including institutional websites, situation reports, press releases, and social media accounts, with supplementary details obtained from news articles. A data availability score was calculated for each imported case in terms of how many indicators (sex, age, travel history, date of arrival in country, reporting date of confirmation, and how detected) could be identified. We assessed the relationship between time to first importation and overall Global Health Security Index (GHSI) using Cox regression. K-means clustering grouped countries according to healthcare capacity and health and demographic risk factors. ResultsA total of 13,201 confirmed cases of COVID-19 were reported by 48 countries in SSA during the 54 days following the first known introduction to the region. Out of the 2516 cases for which travel history information was publicly available, 1129 (44.9%) were considered importation events. At the regional level, imported cases tended to be male (65.0%), were a median 41.0 years old (Range: 6 weeks - 88 years), and most frequently had recent travel history from Europe (53.1%). The median time to reporting an introduction was 19 days; a countrys time to report its first importation was not related to GHSI, after controlling for air traffic. Countries that had, on average, the highest case fatality rates, lowest healthcare capacity, and highest probability of premature death due to non-communicable diseases were among the last to report any cases. ConclusionsCountries with systemic, demographic, and pre-existing health vulnerabilities to severe COVID-related morbidity and mortality are less likely to report any cases or may be reporting with limited public availability of information. Reporting on COVID detection and response efforts, as well as on trends in non-COVID illness and care-seeking behavior, is critical to assessing direct and indirect consequences and capacity needs in resource-constrained settings. Such assessments aid in the ability to make data-driven decisions about interventions, country priorities, and risk assessment. Key MessagesO_LIWe line-listed epidemiological indicators for the initial cases reported by 48 countries in sub-Saharan Africa by reviewing and synthesizing information provided by official institutional outlets and news sources. C_LIO_LIOur findings suggest that countries with the largest proportions of untreated comorbidities, as measured by probability of premature death due to non-communicable diseases, and the fewest healthcare resources tended to not be reporting any cases at one-month post-introduction into the region. C_LIO_LIUsing data availability as a measure of gaps in detection and reporting and relating them to COVID-specific parameters for morbidity and mortality provides a measure of vulnerability. C_LIO_LIAccurate and available information on initial cases in seeding local outbreaks is key to projecting case counts and assessing the potential impact of intervention approaches, such that support for local data teams will be important as countries make decisions about control strategies. C_LI
